Towards an open-source semantic data infrastructure for integrating clinical and scientific data in cognition-guided surgery

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

  • Andreas Fetzer - , German Cancer Research Center (DKFZ) (Author)
  • Jasmin Metzger - , German Cancer Research Center (DKFZ) (Author)
  • Darko Katic - , Karlsruhe Institute of Technology (Author)
  • Keno März - , German Cancer Research Center (DKFZ) (Author)
  • Martin Wagner - , University Hospital Heidelberg (Author)
  • Patrick Philipp - , Karlsruhe Institute of Technology (Author)
  • Sandy Engelhardt - , German Cancer Research Center (DKFZ) (Author)
  • Tobias Weller - , Karlsruhe Institute of Technology (Author)
  • Sascha Zelzer - , German Cancer Research Center (DKFZ) (Author)
  • Alfred M. Franz - , German Cancer Research Center (DKFZ) (Author)
  • Nicolai Schoch - , Heidelberg University  (Author)
  • Vincent Heuveline - , Heidelberg University  (Author)
  • Maria Maleshkova - , Karlsruhe Institute of Technology (Author)
  • Achim Rettinger - , Karlsruhe Institute of Technology (Author)
  • Stefanie Speidel - , Karlsruhe Institute of Technology (Author)
  • Ivo Wolf - , Mannheim University of Applied Sciences (Author)
  • Hannes Kenngott - , Heidelberg University  (Author)
  • Arianeb Mehrabi - , Heidelberg University  (Author)
  • Beat P. Müller-Stich - , Heidelberg University  (Author)
  • Lena Maier-Hein - , German Cancer Research Center (DKFZ) (Author)
  • Hans Peter Meinzer - , German Cancer Research Center (DKFZ) (Author)
  • Marco Nolden - , German Cancer Research Center (DKFZ) (Author)

Abstract

In the surgical domain, individual clinical experience, which is derived in large part from past clinical cases, plays an important role in the treatment decision process. Simultaneously the surgeon has to keep track of a large amount of clinical data, emerging from a number of heterogeneous systems during all phases of surgical treatment. This is complemented with the constantly growing knowledge derived from clinical studies and literature. To recall this vast amount of information at the right moment poses a growing challenge that should be supported by adequate technology. While many tools and projects aim at sharing or integrating data from various sources or even provide knowledge-based decision support - to our knowledge - no concept has been proposed that addresses the entire surgical pathway by accessing the entire information in order to provide context-aware cognitive assistance. Therefore a semantic representation and central storage of data and knowledge is a fundamental requirement. We present a semantic data infrastructure for integrating heterogeneous surgical data sources based on a common knowledge representation. A combination of the Extensible Neuroimaging Archive Toolkit (XNAT) with semantic web technologies, standardized interfaces and a common application platform enables applications to access and semantically annotate data, perform semantic reasoning and eventually create individual context-aware surgical assistance. The infrastructure meets the requirements of a cognitive surgical assistant system and has been successfully applied in various use cases. The system is based completely on free technologies and is available to the community as an open-source package.

Details

Original languageEnglish
Title of host publicationMedical Imaging 2016 - PACS and Imaging Informatics
EditorsTessa S. Cook, Jianguo Zhang
PublisherSPIE - The international society for optics and photonics, Bellingham
ISBN (electronic)9781510600249
Publication statusPublished - 2016
Peer-reviewedYes
Externally publishedYes

Publication series

SeriesProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9789
ISSN1605-7422

Conference

TitleMedical Imaging 2016 - PACS and Imaging Informatics: Next Generation and Innovations
Duration28 - 29 February 2016
CitySan Diego
CountryUnited States of America

External IDs

ORCID /0000-0002-4590-1908/work/163294027

Keywords

Keywords

  • Data integration, Knowledge modeling, Ontologies, Open-source, Semantic data infrastructure, Surgery, Surgical assistance